Claes Lundström examines a digital pathology slide. The tools of the future are tested using AI technology and imaging at the national research arena AIDA. If artificial intelligence (AI) is to be of help in healthcare, people and machines must be able to work effectively together. A new study shows that doctors who use AI when examining tissue samples can work faster, while still doing high-quality work. How can AI systems in healthcare be designed to facilitate the interaction between people and computers?

While there obviously shouldn't be an outcry for robots to take the jobs of human physicians, that doesn't mean artificial intelligence can't play an important role when it comes to helping doctors carry out certain aspects of their jobs -- such as recognizing early symptoms of serious diseases that can go unnoticed. A delay in diagnosis can make it more difficult to implement effective treatments or even find cures. This is something that IBM wants to help with, courtesy of a new probabilistic A.I. model that can be used to better understand patients' individual conditions and, crucially, how they are likely to develop. It can give information about a wide range of symptoms -- from shaking hands to mood swings -- and then use this data to help identify the biomarkers of diseases including diabetes, Huntington's disease, Alzheimer's, Parkinson's, and more. The A.I. can help doctors understand more about the progression of these neurological disorders, as well as pinpoint how advanced they are. "What makes this model unique is that it analyzes multiple clinical aspects and symptoms of a neurodegenerative disease at the same time," Soumya Ghosh, a research staff member in the Health Analytics Research Group at IBM Research, told Digital Trends.